Machine Learning Resource Manager, SIML

Apple • Cupertino, CA

2h

About The Position

Our team focuses on building the best possible ecosystem for ML R&D engineers to build Apple-quality ML-based technologies. We develop numerous tools to facilitate development of ML models and collaboration around these ML models, and we manage the use of multiple resources such as training compute for Software Engineering, or disk footprint of on-device ML models throughout our operating systems. This unique blend of tooling and resource management offers a powerful opportunity to enhance the tools that support our policy initiatives. These initiatives span organizational boundaries and influence nearly every engineering team across the company. In this role: you will focus on the resource management role of our team. You will be tasked to support daily operations helping the engineering teams in SWE navigate resource-related concerns as well as interface with the platform teams, capacity planning, and finance teams. You will own the efficiency metrics for the org, both exposing issues and correcting. You will also contribute to improvements on how we manage these resources from a technical and policy standpoint, and how we influence the rest of the company on these aspects. It is a highly cross-functional role with significant exposure to challenges across all aspects of the stack.

Requirements

• Bachelors or Master’s degree or equivalent experience 5+ years of experience in industry
• A proven ability to create, implement, and refine durable, large-scale processes
• Exceptional communication, negotiation, and interpersonal skills, with a talent for building consensus
• A strong generalist mindset with the ability to deconstruct complex problems and drive toward clear, optimized solutions
• Strong technical skills to allow for diving deep when needed
• General understanding of fundamental machine learning concepts and the development lifecycle

Nice To Haves

• Expertise in leading infrastructure strategy for scalable, high-performance ML systems (storage, compute, networking, and benchmarking)
• Demonstrated success in a resource management role within a technical or engineering organization
• Deep, practical knowledge of the modern ML development landscape and its associated challenges
• Programming and technical skills that enable hands-on contributions to tooling and ML systems

What This Job Offers

• Job Type: Full-time
• Career Level: Mid Level